Method and system for sensing an obstacle, and storage medium

ABSTRACT

Embodiments of a method and system for sensing an obstacle, a computer device, and a computer-readable storage medium are provided. The method can include: capturing continuously, by first and second cameras adjacently arranged on a motor vehicle, obstacles around the motor vehicle, to obtain at least a first obstacle image and a second obstacle image respectively; associating the first obstacle image with the second obstacle image; determining whether the first obstacle image and the second obstacle image comprise the same obstacle. By means of some of the disclosed methods and systems, an obstacle can be real-time sensed by a motor vehicle in a large field of view, such as, a range of 360° around the vehicle.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to Chinese Patent Application No.201811039205.5, filed on Sep. 6, 2018, which is hereby incorporated byreference in its entirety.

TECHNICAL FIELD

The present application relates to the field of motor vehicle driving,and in particular, to a method and system for sensing an obstacle, and acomputer storage medium.

BACKGROUND

In existing unmanned vehicles, the road condition in a specific angulardirection is often sensed by a single camera. The visual sensing basedon a single camera is different from that of a laser radar, and thesensing rang is very small, which usually depends on the camera's fieldof view (fov). The camera's field of view (fov) is generally less than180 degrees, and sometimes the field of view can't be too large takingaccount of the sensing distance. Therefore, only the road condition in aspecific angular direction is sensed by a single camera, and an obstaclethat is not in the field of view cannot be sensed. In a case that theobstacle is too close to a main car (an unmanned vehicle), it is easy tocause an accident such as emergency braking and collision. Even worse,during a period when an obstacle just appears in the field of view,because the image box of the obstacle for detection is in a truncatedstate, the image box is not completed, such that the 3D position of theobstacle cannot be estimated accurately. As a result, the velocity ofthe obstacle cannot be estimated accurately by the sensing system, andwrong information is inputted to the decision system of the unmannedvehicle, such that the unmanned vehicle cannot run properly.

SUMMARY

A method, a system and a computer device for sensing an obstacle, and acomputer readable storage medium are provided according to embodimentsof the present application, so as to at least solve the above technicalproblems in the existing technology.

According to a first aspect, a method for sensing an obstacle includes:

capturing continuously, by at least two cameras, obstacles around themotor vehicle, to obtain at least a first obstacle image and a secondobstacle image respectively, wherein the at least two cameras comprisesfirst and second cameras adjacently arranged on a motor vehicle;

associating the first obstacle image with the second obstacle image;

determining whether the first obstacle image and the second obstacleimage include the same obstacle.

In conjunction with the first aspect, in a first implementation of thefirst aspect of the present application, the associating the firstobstacle image with the second obstacle image includes:

associating the first obstacle image with the second obstacle imagebased on an image box feature with respect to the first obstacle imageand the second obstacle image, in a case that a field of view of thefirst camera overlaps with a field of view of the second camera.

In conjunction with the first implementation of first aspect, in asecond implementation of the first aspect of the present application,the associating the first obstacle image with the second obstacle imagebased on an image box feature with respect to the first obstacle imageand the second obstacle image includes:

forming a second image box by projecting a first image box of the firstobstacle image into an imaging plane of the second camera via areference coordinate system, and comparing the second image box with athird image box of the second obstacle image, to determine whether thesecond image box and the third image box include the same obstacleaccording to an image box feature with respect to the second image boxand the third image box.

In conjunction with the first implementation of first aspect, in a thirdimplementation of the first aspect of the present application, in a casethat a field of view of the first camera does not overlap with a fieldof view of the second camera, the first obstacle image is associatedwith the second obstacle image by estimating a motion equation within atime period from a time when the obstacle just disappears from the fieldof view of the first camera to a time when the obstacle just enters thefield of view of the second camera.

In conjunction with the third implementation of first aspect, in afourth implementation of the first aspect of the present application,the associating the first obstacle image with the second obstacle imageincludes:

converting first coordinates of the first image box of the firstobstacle image into reference coordinates of a reference coordinatesystem,

updating continuously the reference coordinates with the estimated ofmotion equation,

projecting the latest updated reference coordinates into an imagingplane of the second camera to obtain second coordinates when theobstacle just enters the field of view of the second camera, and

comparing the second image box of the first obstacle image formed by thesecond coordinates with the third image box of the second obstacle imagecaptured at a time when the obstacle just enters the field of view ofthe second camera, to determine whether the second image box and thethird image box include the same obstacle according to an image boxfeature with respect to the second image box and the third image box.

In conjunction with the fourth implementation of first aspect, in afifth implementation of the first aspect of the present application, theestimating a motion equation includes estimating a motion equation incondition of a uniform motion, a uniformly accelerated motion or auniformly decelerated motion.

In conjunction with a first implementation of the first aspect, a secondimplementation of the first aspect, a fourth implementation of the firstaspect and a fifth implementation of the first aspect, in a sixthimplementation of the first aspect of the present application, the imagebox feature includes a central distance between the second image box andthe third image box, an aspect ratio of each image box, and/or anintersection over union of the second image box and the third image box.

In conjunction with the first aspect, a first implementation of thefirst aspect, a second implementation of the first aspect, a thirdimplementation of the first aspect, in a fourth implementation of thefirst aspect of the present application and a fifth implementation ofthe first aspect, in a seventh implementation of the first aspect of thepresent application, the at least two cameras are arranged on the leftfront, on the left rear, on the front, on the rear, on the right front,and on the right rear of a body of the motor vehicle, respectively, tosense obstacles within 360° around the body of the motor vehicle.

In conjunction with the first aspect, a first implementation of thefirst aspect, a second implementation of the first aspect, a thirdimplementation of the first aspect, in a fourth implementation of thefirst aspect of the present application and a fifth implementation ofthe first aspect, in an eighth implementation of the first aspect of thepresent application, the determining whether the first obstacle imageand the second obstacle image include the same obstacle image includes:

determining whether the first obstacle image and the second obstacleimage include the same obstacle image according to a type of theobstacle, a moving velocity of the obstacle, a moving direction of theobstacle, and/or an image box feature.

According to a second aspect, a system for sensing an obstacle includes:

at least two cameras, configured to continuously capture obstaclesaround the motor vehicle, to obtain at least a first obstacle image anda second obstacle image respectively, wherein the at least two camerascomprises first and second cameras adjacently arranged on a motorvehicle;

an association unit, configured to associate the first obstacle imagewith the second obstacle image; and

a determination unit, configured to determine whether the first obstacleimage and the second obstacle image include the same obstacle.

In conjunction with the second aspect, in a first implementation of thesecond aspect of the present application, the association unit isfurther configured to associate the first obstacle image with the secondobstacle image based on an image box feature with respect to the firstobstacle image and the second obstacle image, in a case that a field ofview of the first camera overlaps with a field of view of the secondcamera.

In conjunction with the first implementation of the second aspect, in asecond implementation of the second aspect of the present application,the association unit is further configured to form a second image box byprojecting a first image box of the first obstacle image into an imagingplane of the second camera via a reference coordinate system, and tocompare the second image box with a third image box of the secondobstacle image, to determine whether the second image box and the thirdimage box include the same obstacle according to an image box featurewith respect to the second image box and the third image box.

In conjunction with the first implementation of second aspect, in athird implementation of the second aspect of the present application,the association unit is further configured to, in a case that a field ofview of the first camera does not overlap with a field of view of thesecond camera, associate the first obstacle image with the secondobstacle image by estimating a motion equation within a time period froma time when the obstacle just disappears from the field of view of thefirst camera to a time when the obstacle just enters the field of viewof the second camera.

In conjunction with the third implementation of second aspect, in afourth implementation of the second aspect of the present application,the association unit is further configured to:

convert first coordinates of the first image box of the first obstacleimage into reference coordinates of a reference coordinate system,

update continuously the reference coordinates with the estimated motionequation,

project the latest updated reference coordinates into an imaging planeof the second camera to obtain second coordinates when the obstacle justenters the field of view of the second camera, and

compare the second image box of the first obstacle image formed by thesecond coordinates with the third image box of the obstacle imagecaptured at a time when the obstacle just enters the field of view ofthe second camera, to determine whether the second image box and thethird image box include the same obstacle according to an image boxfeature with respect to the second image box and the third image box.

In conjunction with the fourth implementation of second aspect, in afifth implementation of the second aspect of the present application,the estimating a motion equation includes estimating a motion equationin condition of a uniform motion, a uniformly accelerated motion or auniformly decelerated motion.

In conjunction with a first implementation of the second aspect, asecond implementation of the second aspect, a fourth implementation ofthe second aspect and a fifth implementation of the second aspect, in asixth implementation of the second aspect of the present application,the image box feature includes a central distance between the secondimage box and the third image box, an aspect ratio of each image box,and/or an intersection over union of the second image box and the thirdimage box.

In conjunction with the second aspect, a first implementation of thesecond aspect, a second implementation of the second aspect, a thirdimplementation of the second aspect, in a fourth implementation of thesecond aspect of the present application and a fifth implementation ofthe second aspect, in a seventh implementation of the second aspect ofthe present application, the at least two cameras are arranged on theleft front, on the left rear, on the front, on the rear, on the rightfront, and on the right rear of a body of the motor vehicle,respectively, to sense obstacles within 360° around the body of themotor vehicle.

In conjunction with the second aspect, a first implementation of thesecond aspect, a second implementation of the second aspect, a thirdimplementation of the second aspect, in a fourth implementation of thesecond aspect of the present application and a fifth implementation ofthe second aspect, in a seventh implementation of the second aspect ofthe present application, the determination unit is further configured todetermine whether the first obstacle image and the second obstacle imageinclude the same obstacle image according to a type of the obstacle, amoving velocity of the obstacle, a moving direction of the obstacle,and/or an image box feature.

In a third aspect, a computer device is provided according to anembodiment of the present application, the computer device includes: oneor more processors; and a storage device configured to store one or moreprograms, wherein the one or more programs, when executed by the one ormore processors, cause the one or more processors to implement the abovemethod.

In a fourth aspect, a computer-readable storage medium is providedaccording to an embodiment of the present application, in which acomputer program is stored, wherein the computer program, when executedby a processor, causes the processor to implement the above method.

By means of the method and system of the present application for sensingan obstacle, for example, an obstacle can be real-time sensed by a motorvehicle in large range of field of view, such as, a 360° range aroundthe vehicle. In the case of large range of field of view, the movementstate (position, velocity, etc.) of an obstacle in a certain range froma motor vehicle, such as an unmanned vehicle, can be integrallydescribed in the method and system for sensing an obstacle. For example,by accurately estimating a position, a velocity, a direction and a typeof an obstacle, the precise information is provided for thedecision-making system of motor vehicles, such as unmanned vehicles, toprevent high-risk such as collisions.

The above summary is for the purpose of the specification only and isnot intended to be limiting in any way. In addition to the illustrativeaspects, embodiments, and features described above, further aspects,embodiments, and features of the present application will be readilyunderstood by reference to the drawings and the following detaileddescription.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, unless otherwise specified, identical referencenumerals will be used throughout the drawings to refer to identical orsimilar parts or elements. The drawings are not necessarily drawn toscale. It should be understood that these drawings depict only someembodiments disclosed in accordance with the present application and arenot to be considered as limiting the scope of the present application.

FIG. 1 schematically shows a schematic diagram of a method for sensingan obstacle according to an embodiment of the first aspect in thepresent application;

FIG. 2 schematically shows a schematic diagram of associating anobstacle image captured by one camera with an obstacle image captured byanother camera according to an embodiment of the first aspect in thepresent application;

FIG. 3 schematically shows a schematic diagram of estimation of motionequation according to an embodiment of the first aspect in the presentapplication;

FIG. 4 schematically shows a schematic diagram of an image box featureaccording to an embodiment of the first aspect in the presentapplication;

FIG. 5 schematically shows a schematic diagram of a motor vehicle aroundwhich cameras are arranged according to an embodiment of the firstaspect in the present application;

FIG. 6 schematically shows a schematic diagram of determining whether anobstacle image captured by one camera and an obstacle image captured byanother camera include the same obstacle according to an embodiment ofthe first aspect in the present application;

FIG. 7 schematically shows a schematic diagram of a scenario wherefields of view of two adjacent camera 1 and camera 2 overlap, accordingto an embodiment of the first aspect in the present application;

FIG. 8 schematically shows a schematic diagram of a scenario wherefields of view of two adjacent camera 1 and camera 2 do not overlap,according to an embodiment of the first aspect in the presentapplication;

FIG. 9 schematically shows a schematic diagram of blending a pluralityof adjacent cameras according to an embodiment of the first aspect inthe present application;

FIG. 10 schematically shows a schematic diagram of system for sensing anobstacle according to an embodiment of the second aspect of the presentapplication;

FIG. 11 schematically shows an embodiment of a computer device accordingto a third aspect of the present application.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The embodiments of the present disclosure will be described in moredetail below with reference to the accompanying drawings. While someembodiments of the present disclosure are shown in the accompanyingdrawings, it should be understood that the present disclosure may beimplemented in various forms and should not be construed as beinglimited to the embodiments set forth herein, instead providing theseembodiments for a more thorough and complete understanding of thepresent disclosure. It should be understood that the accompanyingdrawings and embodiments of the present disclosure are only examples andare not intended to limit the scope of protection of the presentdisclosure.

In the description of the embodiments of the present disclosure, theterm “including” and similar terms thereof shall be understood as openinclusion, i.e., “including, but not limited to”. The term “based on”should be understood as “based at least in part on”. The term “anembodiment” or “the embodiment” should be understood as “at least oneembodiment”. Other explicit and implicit definitions may also beincluded below.

The following is described in detail with reference to FIGS. 1-11 of thepresent application.

FIG. 1 schematically shows a schematic diagram of a method 100 forsensing an obstacle according to an embodiment of the first aspect inthe present application. The method may include the following steps:Step 102, capturing continuously, by first and second cameras adjacentlyarranged on a motor vehicle, obstacles around the motor vehicle, toobtain at least a first obstacle image and a second obstacle imagerespectively; Step 104, associating the first obstacle image with thesecond obstacle image; Step 106, determining whether the first obstacleimage and the second obstacle image include the same obstacle.

It is shown here that at least two adjacent cameras may be arranged onthe motor vehicle, and more cameras may be arranged as required. Forexample, at least two adjacent cameras on the motor vehicle may includea plurality of cameras arranged on the left front, on the left rear, onthe front, on the rear, on the right front, and on the right rear of thebody of the motor vehicle, respectively. As shown in FIGS. 5 and 10, itis possible to sense obstacles in a large field of view such as 360°,around the motor vehicle. Since each camera has its own visual field,i.e., field of view, it can be understood by those skilled in the artthat a plurality of cameras such as 6 cameras or 8 cameras may bearranged as required, in a case that it is required to sense obstaclesin a large field of view or visual field such as 360° around a motorvehicle.

For example, in the schematic diagram shown in FIGS. 5 and 10, eightcameras are arranged around the motor vehicle 8, namely, a camera 2 onthe left front of the body; a camera 1 on the left rear of the body; acamera 3, a camera 4 and a camera 5 on the front of the body; a camera 8on the rear of the body, a camera 6 on the right front of the body, anda camera 7 on the right rear of the body.

The term “obstacles” mentioned in various embodiments of thespecification in the present application may be understood broadly, forexample, pedestrians, bicycles, electric vehicles, other non-motorvehicles or motor vehicles around a motor vehicle may be regarded asobstacles relative to this vehicle (the motor vehicle).

It should be noted that the term “obstacle image” appearing in variousembodiments of the present application, may include multiple obstacleimages. For example, the “obstacle image” may include an image of apedestrian, a bicycle, an electric vehicle, another non-motor vehicle ormotor vehicle, and so on.

The term “camera” mentioned in various embodiments of the specificationin the present application may be understood broadly, for example, the“camera” may include a fish-eye camera, a wide-angle camera, and so on.

The terms “reference coordinate system” and “reference coordinate”mentioned in the embodiments of the specification in the presentapplication may be understood broadly, and may, for example, include avehicle body coordinate in a vehicle body coordinate system, a worldcoordinate in a world coordinate system, and another coordinate system,as long as the conversion relationship of two adjacent cameras to thiscoordinate system is known.

Obstacles around the motor vehicle are captured continuously by at leasttwo adjacent cameras arranged on the motor vehicle, which is helpful tosense obstacles such as other motor vehicles, and is helpful to fullydescribe the movement state (position, velocity, etc.) of an obstaclewithin a specific range from the motor vehicle such as an unmannedvehicle. For example, the precise information is provided for a decisionsystem of a motor vehicle such as an unmanned vehicle by accuratelyestimating the position, velocity, moving direction and type of anobstacle, to avoid high risk such as collision.

FIG. 2 schematically shows a schematic diagram of associating anobstacle image captured by one camera with an obstacle image captured byanother camera according to an embodiment of the first aspect in thepresent application. In an embodiment, the step 104 of associating thefirst obstacle image with the second obstacle image may include thefollowing step: step 108, associating the first obstacle image with thesecond obstacle image based on an image box feature with respect to thefirst obstacle image and the second obstacle image, in a case that afield of view of the first camera overlaps with a field of view of thesecond camera. In an embodiment of the present application, the step 108of associating the first obstacle image with the second obstacle imagebased on an image box feature with respect to the first obstacle imageand the second obstacle image includes: step 110, forming a second imagebox by projecting a first image box of the first obstacle image into animaging plane of the second camera via a reference coordinate system,and comparing the second image box with a third image box of the secondobstacle image, to determine whether the second image box and the thirdimage box include the same obstacle according to an image box featurewith respect to the second image box and the third image box.

The above may specifically refer to FIG. 7. FIG. 7 schematically shows aschematic diagram of a scenario where fields of view of two adjacentcamera 1 and camera 2 overlap, according to an embodiment of the firstaspect in the present application. In FIG. 7, the field of view of acamera 1 is represented by V1, a cross section of the field of view isapproximately a V-shaped cross-section. Similarly, the field of view ofa camera 2 is represented by V2, a cross section of the field of view isalso approximately a V-shaped cross section. There are an overlappingarea A and non-overlapping areas B in V1 and V2, and a non-covering areaC. Here, the case where an obstacle enters the field of view V2 of thecamera 2 from the field of view V1 of the camera 1 through theoverlapping area A will be discussed firstly. The case where an obstacleenters the field of view V2 of the camera 2 from the field of view V1 ofthe camera 1 through the non-covering area C or through thenon-overlapping area B will be described later.

In the above description, in step 108, i.e. the first obstacle image isassociated with the second obstacle image based on an image box featurewith respect to the first obstacle image and the second obstacle image,in a case that a field of view of the first camera overlaps with a fieldof view of the second camera. The reason for associating the obstacleimages based on image box feature of the obstacle images captured by theat least two adjacent cameras is to compare the obstacle images capturedby the adjacent cameras such as the camera 1 and the camera 2. As acaptured frame image may include image boxes of a plurality of obstaclessuch as pedestrians, non-motor vehicles, other motor vehicles, and soon, associating the obstacle images captured by the adjacent cameras isto associate the image boxes of the same obstacle which are initiallydetermined, for example, to associate the image box of a pedestrianimage captured by the camera 1 with the image box of a pedestrian imagecaptured by camera 2, to associate the image box of a bicycle imagecaptured by the camera 1 with the image box of a bicycle image capturedby the camera 2, to associate the image box of another motor vehicleimage captured by the camera 1 with the image box of another motorvehicle image captured by the camera 2, etc.

For the above-mentioned step 110: a second image box is formed byprojecting a first image box of the first obstacle image into an imagingplane of the second camera via a reference coordinate system, and thesecond image box is compared with a third image box of the secondobstacle image, to determine whether the second image box and the thirdimage box include the same obstacle according to an image box featurewith respect to the second image box and the third image box, it shouldbe noted here that the reference coordinate system is a generalizedconcept. The reference coordinate system may include the vehicle bodycoordinate of the vehicle body coordinate system and the worldcoordinate of the world coordinate system, as long as the conversionrelationship of two adjacent cameras to this coordinate system is known,as already described above. The following is a brief description of theworld coordinate system as an example.

For example, the first coordinates (u1, v1) in the imaging plane of thecamera 1 can be converted into the world coordinates P (x1, y1, z1) inthe world coordinate system via the rotation and translation matrixes R1and T1, and then the world coordinates P (x1, y1, z1) can be convertedinto the second coordinates in the imaging plane of the camera 2 via therotation and translation matrixes R2 and T2. For example, the firstcoordinates (u1, v1) of the first point in the image box of the obstacleimage captured by the camera 1 can be converted into the worldcoordinates P1 (x1, y1, z1) in the world coordinate system via therotational translation matrixes R1 and T1, and then the worldcoordinates P1 (x1, y1, z1) can be converted into the second coordinates(u12, v12) of the first point in the imaging plane of the camera 2 viathe rotation and translation matrixes R2 and T2, thereby completing theprojection of the first point. Similarly, the first coordinates (u2, v2)of the second point in the image box of the obstacle image captured bythe camera 1 can be converted into the world coordinates P2 (x2, y2, z2)in the world coordinate system via the rotation and translation matrixesR1′ and T1′, and then the world coordinates P2 (x2, y2, z2) can beconverted into the second coordinates (u22, v22) of the second point inthe imaging plane of the camera 2 via the rotation and translationmatrixes R2′ and T2′, thereby completing the projection of the secondpoint. Similarly, the first coordinates (u3, v3) of the third point inthe image box of the obstacle image captured by the camera 1 can beconverted into the world coordinates P3 (x3, y3, z3) in the worldcoordinate system via the rotation and translation matrixes R1″ and T1″,and then the world coordinates P3 (x3, y3, z3) can be converted into thesecond coordinates (u32, v32) of the third point in the imaging plane ofthe camera 2 via the rotation and translation matrix R2″ and T2″,thereby completing the projection of the third point, etc.

After converting all the first coordinates of the key points in thefirst image box of the obstacle image captured by the camera 1 into thesecond coordinates of the key points in the second image box of theimaging plane of the camera 2 via the world coordinate system, the taskof projecting the first image box of the obstacle image captured by thecamera 1 into the imaging plane of the camera 2 via the referencecoordinate system is completed.

It is known how to convert the first coordinates of the key points inthe first image box of the obstacle image captured by the camera 1 intothe world coordinates in the world coordinate system, and how to convertthe world coordinates into the second coordinates of the key points inthe second image box in the imaging plane of the camera 2, which are notthe major concepts of the present application, and hence are notdescribed herein again.

FIG. 8 schematically shows a schematic view of a scenario where fieldsof view of two adjacent camera 1 and camera 2 do not overlap, accordingto an embodiment of the first aspect in the present application. Thearea C shown in FIG. 7 is a non-covering area which is not covered bythe fields of view of two adjacent camera 1 and camera 2. Similarly, asshown in FIG. 8, the field of view of the camera 1 is represented by V1,a cross section of the field of view is approximately a V-shaped crosssection; similarly, the field of view of the camera 2 is represented byV2, a cross section of the field of view is also approximately aV-shaped cross section.

Referring back to FIG. 2, FIG. 2 shows step 112 of associating the firstobstacle image with the second obstacle image by estimating a motionequation within a time period from a time when the obstacle justdisappears from the field of view of the first camera to a time when theobstacle just enters the field of view of the second camera, in a casethat a field of view of the first camera does not overlap with a fieldof view of the second camera. Further, the step 112 of associating thefirst obstacle image with the second obstacle image may further includestep 114 of converting first coordinates of the first image box of thefirst obstacle image into reference coordinates of a referencecoordinate system; updating continuously the reference coordinates withthe estimated motion equation; projecting the latest updated referencecoordinates into an imaging plane of the second camera to obtain secondcoordinates when the obstacle just enters the field of view of thesecond camera; and comparing the second image box of the first obstacleimage formed by the second coordinates with the third image box of thesecond obstacle image captured at a time when the obstacle just entersthe field of view of the second camera, to determine whether the secondimage box and the third image box include the same obstacle according toan image box feature with respect to the second image box and the thirdimage box.

As mentioned above, in the case that the fields of view V1 and V2 of twoadjacent cameras do not overlap, as shown in FIG. 8, or in thenon-covering area C which is not covered by the fields of view V1 and V2of two adjacent cameras, as shown in FIG. 7, a motion equation isestimated to associate the obstacle images within a time period from atime when the obstacle just disappears from the field of view V1 of thecamera 1 to a time when the obstacle just enters the field of view V2 ofthe other camera 2. Here, the obstacle may be moving within a timeperiod from a time when the obstacle just disappears from the field ofview V1 of the camera 1 to a time when the obstacle just enters thefield of view V2 of the other camera 2. Since the obstacle cannot becaptured and tracked by any cameras during this time period, a motionequation for the movement of the obstacle in this time period needs tobe estimated. The conditions where the motion equation is estimated areshown in FIG. 3. For example, estimating the motion equation 116 mayinclude estimating the motion equation in condition of a uniform motion118, estimating the motion equation in condition of a uniformlyaccelerated motion 120 or estimating the motion equation in condition ofa uniformly decelerated motion 122, and so on.

As mentioned above, the first coordinates (u1, v1) of the first point inthe image box of the obstacle image captured by the camera 1 areconverted into the reference coordinates P (x1, y1, z1) of the referencecoordinate system, and then the reference coordinates P (x1, y1, z1) arecontinuously updated with the estimation of motion equation. Forexample, assuming that the obstacle is moving at a uniform velocity, theupdated reference coordinates of the first point are P (x1+vt, y1+vt,z1+vt), where v is the moving velocity of the obstacle, t is a timeperiod from a time when the obstacle just leaves the field of view V1 ofthe camera 1 to the current time, and in a case that the obstacle justenters the field of view V2 of the camera 2, t represents the timeperiod from a time when the obstacle just leaves the field of view V1 ofthe camera 1 to a time when the obstacle just enters the field of viewV2 of the camera 2. Similarly, the first coordinates (u2, v2) of thesecond point in the image box of the obstacle image captured by thecamera 1 are converted into the reference coordinates P (x2, y2, z2) ofthe reference coordinate system, and then the reference coordinates P(x2, y2, z2) are continuously updated with the estimation of motionequation. For example, assuming that the obstacle is moving at a uniformvelocity, the updated reference coordinates of the second point are P(x2+vt, y2+vt, z2+vt), where v is the moving velocity of the obstacle, tis the time period from a time when the obstacle just leaves the fieldof view V1 of the camera 1 to the current time, and in a case that theobstacle just enters the field of view V2 of the camera 2, t representsthe time period from a time when the obstacle just leaves the field ofview V1 of the camera 1 to a time when the obstacle just enters thefield of view V2 of the camera 2. The first coordinates (u3, v3) of thethird point in the image box of the obstacle image captured by thecamera 1 are converted into the reference coordinates P (x3, y3, z3) ofthe reference coordinate system, and then the reference coordinates P(x3, y3, z3) are continuously updated with the estimation of motionequation. For example, assuming that the obstacle is moving at a uniformvelocity, the updated reference coordinates of the third point are P(x3+vt, y3+vt, z3+vt), where v is the moving velocity of the obstacle, tis a time period from a time when the obstacle just leaves the field ofview V1 of the camera 1 to the current time, and in a case that theobstacle just enters the field of view V2 of the camera 2, t representsthe time period from a time when the obstacle just leaves the field ofview V1 of the camera 1 to a time when the obstacle just enters thefield of view V2 of the camera 2, and the like.

After all the reference coordinates of the key points in the image boxof the obstacle image captured by the camera 1 are updated to the latestreference coordinates, the step of continuously updating the referencecoordinates with the estimation of the motion equation is completed.

When an obstacle just enters the field of view V2 of the other camera,the latest updated reference coordinates such as P (x1+vt, y1+vt,z1+vt), P (x2+vt, y2+vt, z2+vt), P (x3+vt, y3+vt, z3+vt), are projectedto the second coordinates such as (u12, v12), (u22, v22), (u32, v32) inthe imaging plane of the other camera, and the second image box of theobstacle image, formed by the second coordinates, is compared with thethird image box of the obstacle image captured by the other camera, todetermine whether the second image box and the third image box includethe same obstacle.

The above is described in the case of a uniform motion of the obstacle.Similar methods can be applied in the cases of a uniformly acceleratedmotion, a uniformly decelerated motion and even a static state of theobstacle, in particular, the second image box of the obstacle imageformed by the second coordinates is compared with the third image box ofthe obstacle image captured by another camera, to determine whether thetwo image boxes include the same obstacle according to the image boxfeature of the two image boxes.

A schematic diagram of image box feature 124 is shown in FIG. 4. Forexample, the image box feature 124 may include a central distance 126between an image box (i.e., the second image box) in an imaging plane(formed by an obstacle image) of another camera and an image box (i.e.,the third image box) of the obstacle image captured by the other camera,an aspect ratio 128 of each image box, and/or an intersection over unionof the second image box and the third image box 130.

It should be noted that the first image box of the obstacle imagecaptured by the camera 1 is projected into the imaging plane of anothercamera 2 via the reference coordinate system to form the second imagebox, which is often different from the third image box of the obstacleimage captured by the other camera 2 itself. For example, the secondimage box and the third image box do not overlap completely, so there isa central distance between a center of the second image box of theobstacle image and a center of the third image box of the obstacle imagecaptured by the other camera 2 itself. The central distance is one ofthe indicators for determining whether the second image box and thethird image box include the same obstacle. For example, in a case thatthe central distance is less than a specific threshold, the two imageboxes are determined to be for the same obstacle. A specific thresholdcan be determined according to the circumstances.

The aspect ratio 128 of each image box is also one of the indicators fordetermining whether the second image box and the third image box includethe same obstacle. The closer the aspect ratios of the image boxes are,the more likely the two image boxes are captured for the same obstacle.Similarly, in a case that the aspect ratio 128 of each image box isabove a specific threshold, the two image boxes are determined to be forthe same obstacle. A specific threshold can be determined according tothe circumstances.

The intersection over union 130 refers to the overlapping ratio betweenthe second image box of the obstacle image and the third image box ofthe obstacle image captured by the other camera 2 itself, that is, theratio of their intersection to union. The closer the ratio of theintersection over union is to 1, the more likely the two image boxes arecaptured for the same obstacle. Similarly, in a case that the ratio ofthe intersection over union is above a specific threshold, the two imageboxes are determined to be for the same obstacle. A specific thresholdcan be determined according to the circumstances.

In an embodiment of the present application, as shown in FIG. 6, step106 of determining whether the first obstacle image and the secondobstacle image include the same obstacle may further include, forexample, determining according to a type of the obstacle 132,determining according to a moving velocity of the obstacle 134,determining according to a moving direction of the obstacle 136, and/ordetermining according to an image box feature 138.

The determining according to a type of an obstacle 132 is, for example,assuming that the obstacle tracked and captured by the camera 1 is apedestrian, the displayed image box of the obstacle (i.e., the firstimage box) corresponds to the pedestrian, while the image captured by anadjacent camera 2 includes both the image box of a pedestrian (i.e., thethird image box) and the image box of a bicycle. It is sufficient toobtain the image box of the pedestrian in the field of view of thecamera 2 (i.e., the second image box) by projecting the first image boxinto the field of view of the camera 2, and match the second image boxwith the third image box, to determine whether the pedestrian obstacleimage captured by the camera 1 and the pedestrian obstacle imagecaptured by the camera 2 include the same obstacle.

Similarly, assuming that the obstacle captured by the camera 1 is abicycle, the displayed image box of the obstacle (i.e., the first imagebox) corresponds to the bicycle, while the image captured by an adjacentcamera 2 includes both the image box of a bicycle (i.e., the third imagebox) and the image box of a pedestrian. It is sufficient to obtain theimage box of the bicycle in the field of view of the camera 2 (i.e., thesecond image box) by projecting the first image box into the field ofview of the camera 2, and match the second image box with the thirdimage box, to determine whether the bicycle obstacle image captured bythe camera 1 and the bicycle obstacle image captured by the camera 2include the same obstacle.

It should be noted, no matter whether the fields of view of the adjacentcameras overlap or not, step 106 of determining whether the firstobstacle image and the second obstacle image include the same obstacleimage includes: forming a second image box by projecting a first imagebox of the first obstacle image into an imaging plane of the secondcamera, and then comparing the second image box with a third image boxof the second obstacle image, to determine whether the second image boxand the third image box include the same obstacle according to an imagebox feature.

Determining according to a moving velocity of an obstacle 134 indicatesthat the image captured by a camera includes pedestrians, bicycles,other motor vehicles, trees, and so on. The velocities of these objectsare inconsistent. For example, a pedestrian image is captured by thecamera 1, and the image box of the pedestrian image is projected intothe field of view of the camera 2 to obtain an image box of thepedestrian in the field of view of the camera 2. The moving velocity ofa first pedestrian is often different from that of a second pedestrian,so it may be determined whether the first obstacle image captured by thecamera 1 and the second obstacle image captured by the camera 2 includethe same pedestrian obstacle.

The determining according to the image box feature 138 can refer to theintroduction of the image box feature as described above, so it may bedetermined whether the obstacle image captured by the camera 1 and theobstacle image captured by the camera 2 include the same obstacle.

Here is only a description of adjacent camera 1 and camera 2 asexamples. It can be understood by those skilled in the art that theassociation between adjacent camera 2 and camera 3, between adjacentcamera 3 and camera 4, between adjacent camera 4 and camera 5, betweenadjacent camera 5 and camera 6, between adjacent camera 6 and camera 7,between adjacent camera 7 and camera 8, and between adjacent camera 8and camera 1 can refer to the manner of association between camera 1 andcamera 2. For example, the association in the case that the fields ofview of adjacent cameras overlap, and the association in the case thatthe fields of view of adjacent cameras do not overlap, are described indetail above.

FIG. 9 schematically shows a schematic diagram of blending a pluralityof adjacent cameras according to an embodiment of the first aspect inthe present application. For example, a detection box 140 represents animage box of an obstacle tracked by a camera. A multi-target trackingsystem 142 is formed by means of multiple cameras, for example,simultaneously tracking pedestrians, bicycles, electric cars, trees,other motor vehicles and non-motor vehicles, etc. By means of the methodor system for sensing an obstacle according to one aspect of the presentapplication, it is necessary to determine whether blending with acorresponding camera is completed 144, that is, whether the step 106 ofdetermining whether the first obstacle image and the second obstacleimage include the same obstacle is completed. As mentioned above, theassociation or blending is completed until the associations betweenadjacent camera 1 and camera 2, between adjacent camera 2 and camera 3,between adjacent camera 3 and camera 4, between adjacent camera 4 andcamera 5, between adjacent camera 5 and camera 6, between adjacentcamera 6 and camera 7, adjacent camera 7 and camera 8, and betweenadjacent camera 8 and camera 1 are all completed. In a case that all ofthe associations are not yet completed, association between adjacentcameras 146 is continued. If all of the associations are completed, thecurrent tracking result is outputted 148.

It should be noted that the association or blending is completed untilthe above-mentioned associations between the adjacent camera 1 andcamera 2, between the adjacent camera 2 and camera 3, between theadjacent camera 3 and camera 4, between the adjacent camera 4 and camera5, between the adjacent camera 5 and camera 6, between the adjacentcamera 6 and camera 7, between the adjacent camera 7 and camera 8, andbetween the adjacent camera 8 and camera 1 are all completed, which isan embodiment for sensing an obstacle within 360° around the motorvehicle. In some cases, for example, if it is only required to sense theobstacles on the left side of the motor vehicle 8, it is sufficient toassociate between the adjacent camera 8 and camera 1, between theadjacent camera 1 and camera 2, and between the adjacent camera 2 andcamera 3. In some cases, for example, if it is only required to sensethe obstacles on the right side of the motor vehicle 8, it is sufficientto associate between adjacent camera 5 and camera 6, between adjacentcamera 6 and camera 7, and between adjacent camera 7 and camera 8.

According to a second aspect of the present application, a system forsensing an obstacle 300 is provided, as schematically shown in FIG. 10,and may include: at least two adjacent cameras such as cameras 1-8arranged on a motor vehicle 8, the adjacent cameras including first andsecond cameras, configured to continuously capture obstacles around themotor vehicle, to obtain at least a first obstacle image and a secondobstacle image respectively; an association unit 302, configured toassociate the first obstacle image with the second obstacle image; and adetermination unit 304, configured to determine whether the firstobstacle image and the second obstacle image include the same obstacle.

According to an embodiment of the second aspect of the presentapplication, the association unit 302 is further configured to associatethe first obstacle image with the second obstacle image based on animage box feature with respect to the first obstacle image and thesecond obstacle image, in the case that a field of view of the firstcamera overlaps with a field of view of the second camera.

According to another embodiment of the second aspect of the presentapplication, the association unit 302 is further configured to form asecond image box by projecting a first image box of the first obstacleimage into an imaging plane of the second camera via a referencecoordinate system, and to compare the second image box with a thirdimage box of the second obstacle image, to determine whether the secondimage box and the third image box include the same obstacle according toan image box feature with respect to the second image box and the thirdimage box.

According to another embodiment of the second aspect of the presentapplication, the association unit 302 is further configured to, in acase that a field of view of the first camera does not overlap with afield of view of the second camera, associate the first obstacle imagewith the second obstacle image by estimating a motion equation within atime period from a time when the obstacle just disappears from the fieldof view of the first camera to a time when the obstacle just enters thefield of view of the second camera.

According to another embodiment of the second aspect of the presentapplication, the association unit 302 is further configured to

convert first coordinates of the first image box of the first obstacleimage into reference coordinates of a reference coordinate system,

update continuously the reference coordinates with the estimated motionequation,

project the latest updated reference coordinates into an imaging planeof the second camera to obtain second coordinates when the obstacle justenters the field of view of the second camera, and

compare the second image box of the first obstacle image formed by thesecond coordinates with the third image box of the second obstacle imagecaptured at a time when the obstacle just enters the field of view ofthe second camera, to determine whether the second image box and thethird image box include the same obstacle according to an image boxfeature with respect to the second image box and the third image box.

Alternatively, the estimating a motion equation includes estimating amotion equation in condition of a uniform motion, a uniformlyaccelerated motion or a uniformly decelerated motion.

According to an embodiment of the second aspect of the presentapplication, the image box feature may include a central distancebetween the second image box and the third image box, an aspect ratio ofeach image box, and/or an intersection over union of the second imagebox and the third image box.

Alternatively, the at least two cameras are arranged on the left front,on the left rear, on the front, on the rear, on the right front, and onthe right rear of a body of the motor vehicle, respectively, to senseobstacles within 360° around the body of the motor vehicle.

Alternatively, the determination unit is further configured to determinewhether the first obstacle image and the second obstacle image includethe same obstacle image according to a type of the obstacle, a movingvelocity of the obstacle, a moving direction of the obstacle, and/or animage box feature.

According to an embodiment of the third aspect of the presentapplication, a computer device is provided, which may include: one ormore processors; a storage device configured to store one or moreprograms; the one or more programs, when executed by the one or moreprocessors, cause the one or more processors to implement the abovemethod.

According to an embodiment of the fourth aspect of the presentapplication, a computer readable storage medium is provided, in which acomputer program is stored, the computer program, when executed by aprocessor, causes the processor to implement the method described above.

For example, FIG. 11 shows a schematic block diagram of an examplecomputer device 400 that can be used to implement embodiments of thepresent disclosure. It should be understood that a computer device 400may be used to implement a method 100 for sensing an obstacle describedin some embodiments of this disclosure. As shown, the computer device400 includes: a central processing unit (CPU) 402 that can performvarious appropriate actions and processes according to a computerprogram instruction stored in a read-only memory (ROM) 404 or loadedfrom a storage unit 416 into a random access memory (RAM) 406. In theRAM 406, various programs and data required for the operation of thecomputer device 400 can also be stored. The CPU 402, the ROM 404, andthe RAM 406 are connected to each other by a bus 408. An input/output(I/O) interface 410 is also connected to the bus 408.

A plurality of components in the computer device 400 are connected tothe I/O interface 410, the components include: an input unit 412, suchas a keyboard, a mouse, etc.; an output unit 414, such as various typesof displays, speakers, etc.; a storage unit 416, such as a magneticdisk, an optical disk, etc.; and a communication unit 418, such as anetwork card, a modem, a wireless communication transceiver, etc. Thecommunication unit 418 allows the computer device 400 to exchangeinformation/data with other devices through computer networks such asthe Internet and/or various telecommunication networks.

The central processing unit 402 executes the methods and processesdescribed above, such as the method 100. For example, in someembodiments, the method 100 may be implemented as a computer softwareprogram that is materially contained in a machine-readable medium, suchas a storage unit 416. In some embodiments, a part or all of thecomputer program may be loaded into and/or installed on the computerdevice 400 via the ROM 404 and/or the communication unit 418. When acomputer program is loaded into RAM 406 and executed by CPU 62, one ormore actions or steps of method 100 described above may be performed.Alternatively, in other embodiments, the CPU 402 may be configured toexecute the method 100 in any other suitable manner (e.g. by means offirmware).

The functions described above can be performed at least in part by oneor more hardware logic components. For example, types of hardware logiccomponents that can be used are: Field programmable gate arrays (FPGAs),application specific integrated circuits (ASICs), application specificstandard products (ASSPs), system-on-chip systems (SOCs), loadprogrammable logic devices (CPLDs), and the like.

In the description of the specification, the description of the terms“one embodiment,” “some embodiments,” “an example,” “a specificexample,” or “some examples” and the like means the specific features,structures, materials, or characteristics described in connection withthe embodiment or example are included in at least one embodiment orexample of the present application. Furthermore, the specific features,structures, materials, or characteristics described may be combined inany suitable manner in any one or more of the embodiments or examples.In addition, different embodiments or examples described in thisspecification and features of different embodiments or examples may beincorporated and combined by those skilled in the art without mutualcontradiction.

In addition, the terms “first” and “second” are used for descriptivepurposes only and are not to be construed as indicating or implyingrelative importance or implicitly indicating the number of indicatedtechnical features. Thus, features defining “first” and “second” mayexplicitly or implicitly include at least one of the features. In thedescription of the present application, “a plurality of” means two ormore, unless expressly limited otherwise.

Any process or method descriptions described in flowcharts or otherwiseherein may be understood as representing modules, segments or portionsof code that include one or more executable instructions forimplementing the steps of a particular logic function or process. Thescope of the preferred embodiments of the present application includesadditional implementations where the functions may not be performed inthe order shown or discussed, including according to the functionsinvolved, in substantially simultaneous or in reverse order, whichshould be understood by those skilled in the art to which the embodimentof the present application belongs.

Logic and/or steps, which are represented in the flowcharts or otherwisedescribed herein, for example, may be thought of as a sequencing listingof executable instructions for implementing logic functions, which maybe embodied in any computer-readable medium, for use by or in connectionwith an instruction execution system, device, or apparatus (such as acomputer-based system, a processor-included system, or other system thatfetch instructions from an instruction execution system, device, orapparatus and execute the instructions). For the purposes of thisspecification, a “computer-readable medium” may be any device that maycontain, store, communicate, propagate, or transport the program for useby or in connection with the instruction execution system, device, orapparatus. More specific examples (not a non-exhaustive list) of thecomputer-readable media include the following: electrical connections(electronic devices) having one or more wires, a portable computer diskcartridge (magnetic device), random access memory (RAM), read onlymemory (ROM), erasable programmable read only memory (EPROM or flashmemory), optical fiber devices, and portable read only memory (CDROM).In addition, the computer-readable medium may even be paper or othersuitable medium upon which the program may be printed, as it may beread, for example, by optical scanning of the paper or other medium,followed by editing, interpretation or, where appropriate, processotherwise to electronically obtain the program, which is then stored ina computer memory.

It should be understood that various portions of the present applicationmay be implemented by hardware, software, firmware, or a combinationthereof. In the above embodiments, multiple steps or methods may beimplemented in software or firmware stored in memory and executed by asuitable instruction execution system. For example, if implemented inhardware, as in another embodiment, they may be implemented using anyone or a combination of the following techniques well known in the art:discrete logic circuits having a logic gate circuit for implementinglogic functions on data signals, application specific integratedcircuits with suitable combinational logic gate circuits, programmablegate arrays (PGA), field programmable gate arrays (FPGAs), and the like.

Those skilled in the art may understand that all or some of the stepscarried in the methods in the foregoing embodiments may be implementedby a program instructing relevant hardware. The program may be stored ina computer-readable storage medium, and when executed, one of the stepsof the method embodiment or a combination thereof is included.

In addition, each of the functional units in the embodiments of thepresent application may be integrated in one processing module, or eachof the units may exist alone physically, or two or more units may beintegrated in one module. The above-mentioned integrated module may beimplemented in the form of hardware or in the form of softwarefunctional module. When the integrated module is implemented in the formof a software functional module and is sold or used as an independentproduct, the integrated module may also be stored in a computer-readablestorage medium. The storage medium may be a read only memory, a magneticdisk, an optical disk, or the like.

The foregoing descriptions are merely specific embodiments of thepresent application, but not intended to limit the protection scope ofthe present application. Those skilled in the art may easily conceive ofvarious changes or modifications within the technical scope disclosedherein, all these should be covered within the protection scope of thepresent application. Therefore, the protection scope of the presentapplication should be subject to the protection scope of the claims.

What is claimed is:
 1. A method for sensing an obstacle, comprising:capturing continuously, by at least two cameras comprising first andsecond cameras adjacently arranged on a motor vehicle, obstacles aroundthe motor vehicle, to obtain at least a first obstacle image and asecond obstacle image respectively; associating the first obstacle imagecaptured by the first camera with the second obstacle image captured bythe second camera; determining whether the first obstacle image capturedby the first camera and the second obstacle image captured by the secondcamera comprise the same obstacle, wherein in response to determiningthat a field of view of the first camera does not overlap with a fieldof view of the second camera, the first obstacle image captured by thefirst camera is associated with the second obstacle image captured bythe second camera by estimating a motion equation within a time periodfrom a time when the obstacle just disappears from the field of view ofthe first camera to a time when the obstacle just enters the field ofview of the second camera.
 2. The method according to claim 1, whereinthe associating the first obstacle image captured by the first camerawith the second obstacle image captured by the second camera comprises:associating the first obstacle image captured by the first camera withthe second obstacle image captured by the second camera based on animage box feature with respect to the first obstacle image and thesecond obstacle image, in response to determining that a field of viewof the first camera overlaps with a field of view of the second camera.3. The method according to claim 2, wherein the associating the firstobstacle image captured by the first camera with the second obstacleimage captured by the second camera based on an image box feature withrespect to the first obstacle image and the second obstacle imagecomprises: forming a second image box by projecting a first image box ofthe first obstacle image captured by the first camera into an imagingplane of the second camera via a reference coordinate system, andcomparing the second image box with a third image box of the secondobstacle image captured by the second camera, to determine whether thesecond image box and the third image box comprise the same obstacleaccording to an image box feature with respect to the second image boxand the third image box.
 4. The method according to claim 1, wherein theassociating the first obstacle image captured by the first camera withthe second obstacle image captured by the second camera comprises:converting first coordinates of the first image box of the firstobstacle image into reference coordinates of a reference coordinatesystem; updating continuously the reference coordinates with theestimated motion equation; projecting the latest updated referencecoordinates into an imaging plane of the second camera to obtain secondcoordinates when the obstacle just enters the field of view of thesecond camera; and comparing the second image box of the first obstacleimage formed by the second coordinates with the third image box of thesecond obstacle image captured at a time when the obstacle just entersthe field of view of the second camera, to determine whether the secondimage box and the third image box comprise the same obstacle accordingto an image box feature with respect to the second image box and thethird image box.
 5. The method according to claim 4, wherein theestimating a motion equation comprises estimating a motion equation incondition of a uniform motion, a uniformly accelerated motion or auniformly decelerated motion.
 6. The method according to claim 2,wherein the image box feature comprises a central distance between thesecond image box and the third image box, an aspect ratio of each imagebox, and/or an intersection over union of the second image box and thethird image box.
 7. The method according to claim 1, wherein the atleast two cameras are arranged on the left front, on the left rear, onthe front, on the rear, on the right front, and on the right rear of abody of the motor vehicle, respectively, to sense obstacles within 360°around the body of the motor vehicle.
 8. The method according to claim1, wherein the determining whether the first obstacle image captured bythe first camera and the second obstacle image captured by the secondcamera comprise the same obstacle image comprises: determining whetherthe first obstacle image captured by the first camera and the secondobstacle image captured by the second camera comprise the same obstacleimage according to a type of the obstacle, a moving velocity of theobstacle, a moving direction of the obstacle, and/or an image boxfeature.
 9. A system for sensing an obstacle, comprising: at least twocameras comprising first and second cameras adjacently arranged on amotor vehicle, configured to continuously capture obstacles around themotor vehicle, to obtain at least a first obstacle image and a secondobstacle image respectively; one or more processors; and a storagedevice configured to store one or more programs, that, when executed bythe one or more processors, cause the one or more processors to:associate the first obstacle image captured by the first camera with thesecond obstacle image captured by the second camera; and determinewhether the first obstacle image captured by the first camera and thesecond obstacle image captured by the second camera comprise the sameobstacle, wherein the one or more programs, when executed by the one ormore processors, cause the one or more processors further to: inresponse to determining that a field of view of the first camera doesnot overlap with a field of view of the second camera, associate thefirst obstacle image captured by the first camera with the secondobstacle image captured by the second camera by estimating a motionequation within a time period from a time when the obstacle justdisappears from the field of view of the first camera to a time when theobstacle just enters the field of view of the second camera.
 10. Thesystem according to claim 9, wherein the one or more programs, whenexecuted by the one or more processors, cause the one or more processorsfurther to: associate the first obstacle image captured by the firstcamera with the second obstacle image captured by the second camerabased on an image box feature with respect to the first obstacle imageand the second obstacle image, in response to determining that a fieldof view of the first camera overlaps with a field of view of the secondcamera.
 11. The system according to claim 10, wherein the one or moreprograms, when executed by the one or more processors, cause the one ormore processors further to: form a second image box by projecting afirst image box of the first obstacle image captured by the first camerainto an imaging plane of the second camera via a reference coordinatesystem, and to compare the second image box with a third image box ofthe second obstacle image captured by the second camera, to determinewhether the second image box and the third image box comprise the sameobstacle according to an image box feature with respect to the secondimage box and the third image box.
 12. The system according to claim 9,wherein the one or more programs, when executed by the one or moreprocessors, cause the one or more processors further to: convert firstcoordinates of the first image box of the first obstacle image intoreference coordinates of a reference coordinate system, updatecontinuously the reference coordinates with the estimated motionequation, project the latest updated reference coordinates into animaging plane of the second camera to obtain second coordinates when theobstacle just enters the field of view of the second camera, and comparethe second image box of the first obstacle image formed by the secondcoordinates with the third image box of the second obstacle imagecaptured at a time when the obstacle just enters the field of view ofthe second camera, to determine whether the second image box and thethird image box comprise the same obstacle according to an image boxfeature with respect to the second image box and the third image box.13. The system according to claim 12, wherein the estimating a motionequation comprises estimating a motion equation in condition of auniform motion, a uniformly accelerated motion or a uniformlydecelerated motion.
 14. The system according to claim 10, wherein theimage box feature comprises a central distance between the second imagebox and the third image box, an aspect ratio of each image box, and/oran intersection over union of the second image box and the third imagebox.
 15. The system according to claim 9, wherein the at least twocameras are arranged on the left front, on the left rear, on the front,on the rear, on the right front, and on the right rear of a body of themotor vehicle, respectively, to sense obstacles within 360° around thebody of the motor vehicle.
 16. The system according to claim 9, whereinthe one or more programs, when executed by the one or more processors,cause the one or more processors further to: determine whether the firstobstacle image captured by the first camera and the second obstacleimage captured by the second camera comprise the same obstacle imageaccording to a type of the obstacle, a moving velocity of the obstacle,a moving direction of the obstacle, and/or an image box feature.
 17. Anon-transitory computer-readable storage medium, in which a computerprogram is stored, wherein the computer program, when executed by aprocessor, causes the processor to implement the method of claim 1.